E3 Journal of Biotechnology and Pharmaceutical Research
E3 Journal of Biotechnology and Pharmaceutical Research Vol. 3 (3) pp. 62-68, May 2012; © E3 Journals; ISSN 2141-7474
Prediction of bioelectricity production by neural network
Ali Tardast 1 , Mostafa Rahimnejad 1 * , Ghasem Najafpour 1 , Kasra Pirzade 1 , Nader Mokhtarian 21 Biotechnology Research Laboratory, Faculty of Chemical Engineering, Noshirvani University, Babol, Iran
2 Islamic Azad Universtiy, Shahraza Branch, Isfhan, Iran
*Corresponding Author E-mail: Rahimnejad@nit.ac.ir, rahimnejad_mostafa@yahoo.com
Accepted 19 May 2012
Abstract
Microbial fuel cell (MFC) is a new advance technology for production of green electricity from different resources. This technology is able to treat biodegradable organic matter and generate bio-electricity simultaneously. Electrons and protons produce with oxidation of organic matter and then electrons move from external resistance while protons transfer across membrane and reaction between electron, proton and oxygen produce water on the cathode surface. Different kinds of configurations are developed for microbial fuel cell such as the dual and single chamber with membrane and without membrane. In this recent study, artificial neural network was implemented for prediction of fabricated MFC performances. A multilayer perceptron was used which results of prediction were shown a good fit between actual and prediction data with negligible mean square error. Artificial neural network was utilized interconnected mathematical nodes or neurons to form a network that can model complex functional relationship.
Keywords: Artificial neural network, Multilayer perceptron, Microbial Fuel cell.
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